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vbcherepanov

total-agent-memory

memory_relate

Creates a typed link between two knowledge records to expand graph-based search. Supports relation types: causal, solution, context, related, and contradicts.

Instructions

Create a typed relation between two knowledge records. Enriches graph expansion in Tier 4 search. Types: causal, solution, context, related, contradicts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesRelation type
to_idYesTarget knowledge record ID
from_idYesSource knowledge record ID

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate a non-read-only, non-idempotent, non-destructive operation. The description's 'Create' aligns with these, and it adds the graph expansion context. However, it does not disclose side effects like whether duplicates are prevented, ID existence checks, or return behavior, so it adds minimal value beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences, front-loaded with the core action. The types list is redundant with the schema but doesn't bloat it. No fluff; concise enough for quick scanning.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the agent doesn't know what the tool returns. The description doesn't mention return value, error conditions, or prerequisites (e.g., IDs must exist). For a write operation of moderate complexity, this is adequate but not complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% – each parameter has a description in the schema. The description repeats the enum types (causal, solution, etc.) but adds no new meaning beyond what the schema already provides. It doesn't explain how from_id/to_id relate semantically beyond 'source' and 'target'.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Create a typed relation') and the resource ('between two knowledge records'), with a specific list of relation types. It distinguishes itself from sibling tools like memory_save or memory_update by focusing on relations, though it does not explicitly differentiate from kg_add_fact which might overlap.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives a context hint ('Enriches graph expansion in Tier 4 search') but no explicit when-to-use vs alternatives. The purpose implies usage for linking records, but there is no guidance on when not to use it or which alternative to pick, so it's only implied.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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